Research projects

GEOMEDIA, Observatoire des flux géomédiatiques internationaux, 2013-2015. Interdisciplinary project of the French National Research Agency (ANR-GUI-APP-04) bringing together geographers and media experts from the International College of Territorial Sciences and computer scientists from the Grenoble Informatics Laboratory. My role in this project consists in providing abstraction tools (WP3) for the spatial and temporal analysis of international relations through print media (WP4). See my video regarding this project (with english subtitles).

SONGS, Simulation Of Next Generation Systems, 2012-2015. Computer science project of the French National Research Agency (ANR-11-INFRA-13) interested in the simulation of large-scale distributed computing platforms. My role in this project consists in providing abstraction tools to tackle and visualise very large execution traces (WP7). In particular, it leads to the implementation of an aggregation unit within the open-source VIVA software for traces analysis.

Timothée Giraud, Claude Grasland, Robin Lamarche-Perrin, Yves Demazeau and Jean-Marc Vincent. Identification of International Media Events by Spatial and Temporal Aggregation of RSS Flows of Newspapers. Application to the Case of the Syrian Civil War between May 2011 and December 2012. In Proceedings of the 18th European Colloquium on Theoretical and Quantitative Geography (ECTQG'13), p. 112-114, Dourdan, France, Sep. 2013. (proceedings)

Research Interests in Computer Science

My PhD began in October 2010 in the computer science laboratory of Grenoble named LIG (Laboratoire d'Informatique de Grenoble). My thesis is supervised by Yves Demazeau from the MAGMA team and by Jean-Marc Vincent from the MESCAL team. My work is funded by a grant attributed by the Ministry of Higher Education and Research to the UdG (Université de Grenoble).

This Ph.D. thesis is interested in the observation and the analysis of natural or artificial systems. When it comes to large-scale or very complex systems, the observation of microscopic dynamics may suffer technical and semantic limits: How to observe a million of distributed entities? How to interpret such a cluttered microscopic description? The concept of epistemological emergence inherited from philosophy, and more particularly from epistemology, offers an interesting theoretical framework to tackle this issue. Since microscopic analysis is not sufficient to explain complex phenomena, scientists need to define and use high-level abstractions to globally represent the system. Abstractions are thus interpreted as macroscopic observation patterns that reduce the system’s microscopic complexity.

In this thesis, we focus on a particular abstraction process, namely data aggregation. For the abstractions to be interpretable at scale, we propose to quantify and control the complexity reduction and the information losses induced by this aggregation process. Feedback techniques, using measures from information theory, guarantee that the observer is able to properly interpret the generated macroscopic descriptions. Moreover, to be meaningful, aggregation should fit with the semantic properties of the observed system. Exogenous constraints from the expert domain are exploited to lead the abstraction process. Thus, our aggregation technique allows to build multi-resolution descriptions of the system that both preserve its information content and its semantic properties.

The technical contribution of our approach is demonstrated with the analysis of large-scale parallel applications from High Performance Computing. The aggregation technique is successfully applied to the spatial aggregation of one million processes. It reveals anomalies at different levels without going through the complete visualisation of the microscopic level. The semantic contribution is evaluated within an interdisciplinary project (GEOMEDIA) interested in the understanding of international relations through print media analysis. Spatial and temporal aggregation allows to detect critical events at different scales, thus building strong abstractions to describe the local and global dynamics of the underlying social system. We also work on the observation of large-scale complex Multi-agent Systems. In this case, the aggregation process is itself an emergent process. The aggregation algorithms are distributed in space and time and directly provides macroscopic descriptions of the system, without observing in details all the agents.

Research Interests in Philosophy

I recently obtained a Master degree in philosophy at the UPMF (Université Pierre-Mendès-France, Grenoble) under the supervision of Dennis Perrin from the PLC laboratory. I am there interested in the relationship between Artificial Intelligence (AI) and philosophy of mind as particular cases of collaborations between science and philosophy. Thereby, I work on particular interdisciplinary topics such as the concept of emergence and the concept of representation in AI.